In addition to the detection performance, two essential considerations are involved in implementing a hate speech detection model–bias and explainability. Hate speech should not be judged by any specific word but by the context in which the word is used. Even if any word generally considered vicious does not exist in a text, the text can be hate speech. A specific expression does not always imply hatred either (e.g., e.g., `nigger') [1]}. However, the presence of this word can cause a model to make a biased detection of hate speech. This erroneous judgment may inadvertently strengthen the discrimination against the target group of the expression [2]}, [3]}. In this respect, the model's bias toward specific expressions should be excluded.
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